#!/usr/bin/env python3
"""
视频字幕解析服务
用于解析视频中的字幕内容
"""

from flask import Flask, request, jsonify
import time
import uuid
import os
import json
import tempfile
import logging

# 配置日志
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)

app = Flask(__name__)

# 配置上传文件夹
UPLOAD_FOLDER = os.path.join(tempfile.gettempdir(), 'video_uploads')
if not os.path.exists(UPLOAD_FOLDER):
    os.makedirs(UPLOAD_FOLDER)

app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
app.config['MAX_CONTENT_LENGTH'] = 500 * 1024 * 1024  # 限制上传大小为500MB

def extract_subtitles_from_video(video_path):
    """
    从视频中提取字幕
    这里是一个示例实现，实际项目中可以使用如下工具：
    - ffmpeg: 提取嵌入式字幕
    - speech_recognition: 语音识别
    - whisper: OpenAI的语音识别模型
    - pysrt: 处理SRT字幕文件
    """
    logger.info(f"开始从视频中提取字幕: {video_path}")
    
    try:
        # 这里是模拟字幕提取过程
        # 在实际项目中，您可以使用以下命令行调用ffmpeg提取字幕：
        # import subprocess
        # result = subprocess.run([
        #     'ffmpeg', '-i', video_path, '-map', '0:s:0', '-c', 'copy', 
        #     os.path.join(os.path.dirname(video_path), 'subtitle.srt')
        # ], capture_output=True, text=True)
        
        # 或者使用whisper进行语音识别：
        # import whisper
        # model = whisper.load_model("base")
        # result = model.transcribe(video_path)
        # subtitle_text = result["text"]
        
        # 模拟处理时间
        time.sleep(5)
        
        # 返回模拟的字幕内容
        return {
            "success": True,
            "subtitle": "00:00:01,000 --> 00:00:05,000\n这是一段示例字幕内容\n\n00:00:06,000 --> 00:00:10,000\n实际项目中会根据视频内容生成真实字幕\n\n00:00:11,000 --> 00:00:15,000\n可以使用语音识别技术将语音转换为文本",
            "format": "srt"
        }
    except Exception as e:
        logger.error(f"字幕提取失败: {str(e)}")
        return {
            "success": False,
            "error": str(e)
        }

@app.route('/parse_subtitle', methods=['POST'])
def parse_subtitle():
    """处理视频字幕解析请求"""
    try:
        logger.info("收到字幕解析请求")
        
        # 检查是否有文件上传
        if 'file' not in request.files:
            logger.error("没有上传文件")
            return jsonify({
                "success": False,
                "message": "没有上传文件"
            }), 400
        
        file = request.files['file']
        
        # 检查文件名是否为空
        if file.filename == '':
            logger.error("文件名为空")
            return jsonify({
                "success": False,
                "message": "文件名为空"
            }), 400
        
        # 获取任务ID
        task_id = request.form.get('task_id', str(uuid.uuid4()))
        
        # 保存上传的文件
        filename = file.filename
        file_path = os.path.join(app.config['UPLOAD_FOLDER'], f"{task_id}_{filename}")
        file.save(file_path)
        logger.info(f"文件已保存: {file_path}")
        
        # 解析字幕
        subtitle_result = extract_subtitles_from_video(file_path)
        
        # 添加任务ID到结果中
        subtitle_result["task_id"] = task_id
        
        # 清理临时文件
        try:
            os.remove(file_path)
            logger.info(f"临时文件已删除: {file_path}")
        except Exception as e:
            logger.warning(f"删除临时文件失败: {str(e)}")
        
        logger.info(f"字幕解析完成: {task_id}")
        return jsonify(subtitle_result)
        
    except Exception as e:
        logger.error(f"处理请求时出错: {str(e)}")
        return jsonify({
            "success": False,
            "message": f"处理请求失败: {str(e)}"
        }), 500

@app.route('/health', methods=['GET'])
def health():
    """健康检查接口"""
    return jsonify({
        "status": "healthy",
        "service": "subtitle-service",
        "timestamp": time.time()
    })

if __name__ == '__main__':
    logger.info("启动视频字幕解析服务...")
    logger.info("服务地址: http://127.0.0.1:5001")
    logger.info("字幕解析接口: POST /parse_subtitle")
    logger.info("健康检查接口: GET /health")
    app.run(host='0.0.0.0', port=5001, debug=True)